Date: March 9, 2018
Time: 11:30-12:30PM ET
Where: Virtual SEI https://www.ustream.tv/sei
What has been the source of the U.S. defense’s advantage? Pointing to the 1970s-era second offset strategy, some say that the DoD’s true advantage rests in an ability to rapidly field and integrate new technologies at a scale none can match. The second offset strategy, though, was dominated by hardware-based or -reliant technologies, such as GPs positioning and stealth. The third offset strategy will rely on software-dominated, leap-ahead technologies. What does rapidly integrating software innovations look like for the DoD?
In this panel discussion, you will learn
key reasons why DoD struggles to rapidly integrate software innovations
proven ways to bring software innovation to DoD’s doorstep
three software technologies that have been piloted in DoD settings
Jeff Boleng is Acting Chief Technology Officer and a principal researcher at the Carnegie Mellon University Software Engineering Institute (SEI). He joined the SEI in 2012 after 21 years of service as an active-duty cyber-operations officer in the U.S. Air Force. Jeff earned his PhD (2002) and master’s (1997) degrees in mathematical and computer sciences from the Colorado School of Mines and a bachelor’s (1991) degree in computer science from the U.S. Air Force Academy.
Nathan VanHoudnos is a Machine Learning Research Scientist at the SEI. As a data scientist and applied statistician, Nathan focuses on solving problems at the intersection of statistics, machine learning, and cybersecurity. In particular, he develops machine learning solutions for visualization, static analysis, threat analysis, and vulnerability analysis. He received a PhD from Carnegie Mellon University (CMU) in Statistics and Public Policy, as well as MS degrees in Public Policy and Management and Statistics from CMU.
Lena Pons is a Machine Learning Research Scientist at the SEI. Lena researches cyber incident indicator extraction, network anomaly detection and malware analysis. She specializes in in natural language processing, researching relation extraction approaches to augmenting question-answering problems and ontology development. Prior to joining the SEI in 2017, she worked at the National Institutes of Health (NIH), helping to improve a text-mining system for reporting on NIH grant funding. At NIH, she also conducted research into improving coverage of abbreviation extraction methods that extended more broadly into context based methods for resolving ambiguous terms. She received a Master’s in Computer Science from Loyola College in Maryland.
Sam Procter is an Architecture Researcher at the SEI. Sam’s primary research interests are in developing tools that make it easier for people to build safe, correct systems. He recently received his PhD in Computer Science from Kansas State University, where he was a member of the SAnToS Laboratory. His dissertation involved creating an architecturally-based hazard analysis process and tooling for component-based systems.